基于能效优化的用户调度与资源分配算法

该文针对多用户OFDMA移动通信下行系统,提出了基于能效优化的用户调度和资源分配方法。所提方法在满足用户服务质量(QoS)要求的前提下,以最大化系统能效为准则建立优化模型,假设在发射端完全已知信道状态信息(CSI)的情况下,充分利用系统内在的分集,给出了用户调度与速率分配的策略,有效地提高了系统的能量使用效率。仿真结果表明,所提算法的性能在较低复杂度前提下能够取得接近最优算法的性能。     

基于CSS的认知无线电网络PUEA检测和缓解

针对认知无线电网络中的主用户仿真攻击问题,提出了一种基于能量检测的协作频谱感知方法.首先,假设存在一个智能攻击者,它能知道自己所处环境并可以选择不同的传输策略.然后,调整CSS规则和相关参数为能量探测器确定合适且有效的阈值.最后,利用Neyman-Pearson准则进行能量检测,从而检测出恶意攻击.仿真结果表明,相比传统的基于能量检测的频谱感知方法,该方法可以更好地减轻PUEA在频谱感知中的破坏作用.     

基于NOMA的移动边缘计算系统公平能效调度算法

将移动边缘计算技术(MEC)与非正交多址技术(NOMA)结合,同时考虑公平性,该文研究了采用NOMA上行部分卸载的MEC系统公平能效问题。首先将基于公平函数的用户速率与功耗比值定义为公平能效函数,随后提出了两种公平能效调度准则下的能效调度算法,即最大化最小速率准则下DK-SCA算法及最大化系统能效准则下DK-SCALE算法,通过算法实现分别得到两种公平能效调度准则下用户最佳本地CPU处理频率及最佳传输功率。最后通过仿真表明,与基准方案相比,所提基于NOMA的部分卸载方案能够有效地将本地计算和基于NOMA的边缘卸载结合,达到最佳的公平能效性能。     

非高斯噪声下的信号检测算法与性能分析

为改善非高斯背景噪声下的信号检测性能,提出了采用非线性阈值系统的信号检测算法.该算法首先利用阈值系统对接收信号进行预处理,其次采用最小平均错误概率准则对预处理后的信号进行检测,最后推导了所提检测算法的误码率解析表达式并给出仿真验证.理论分析和仿真结果表明:在高斯背景噪声下,线性最佳检测算法的检测性能优于所提检测算法;在非高斯背景噪声下,所提检测算法的检测性能较线性最佳检测算法有显著提升.     

一种高效的协作频谱感知架构

为了有效利用协作频谱感知中的上传时隙以改善感知性能,该文设计一种新的协作频谱感知(CSS)架构。其核心思想是:当一个次用户上传信息时,后面的次用户继续执行本地感知直至轮到其上传时才停止,该方法合理地将一半的空闲上传时隙用于感知,因而更为高效。同时,该文基于Neyman-Pearson准则,研究了AND准则和OR准则下的最优调度策略问题,并讨论了该架构带来的感知性能增益。仿真结果表明:所提架构可以有效改善协作频谱感知性能,而不带来额外的感知时延。     

大规模MIMO OFDMA下行系统能效资源分配算法

针对大规模多输入多输出（MIMO）正交频分多址(OFDMA)下行移动通信系统,提出了一种基于能效最优的资源分配算法。所提算法在采用迫零(ZF)预编码的情况下,以最大化系统能效的下界为准则,同时考虑每个用户的最低速率要求,通过调整带宽分配、功率分配和基站天线数分配来优化能效函数。首先根据优化条件提出了一种迭代算法确定每个用户的带宽分配,然后利用分数规划的性质并采用凸优化方法,通过联合调整基站端的发射天线数和用户的发射功率来优化能效函数。仿真结果表明,所提算法在较少迭代次数的同时能够取得较好的系统能效性能和吞吐量性能。     

多用户大规模MIMO系统能效资源分配算法

该文针对多用户大规模多输入多输出(MIMO)移动通信上行系统,提出一种基于能效优化的资源分配算法。所提方法在采用最大比合并(MRC)接收情况下,满足用户数据速率和可容忍的干扰水平约束条件下,以最大化系统能效下界为准则建立优化模型。根据分数规划的性质,把原始的分数最优化问题转换成减式的形式,进而采用凸优化的方法,通过联合调整基站端的发射天线数和用户的发射功率来优化能效函数。仿真结果表明,所提算法与穷举算法在能效上的差距不足9%,并且有较好的系统频谱效率性能,同时算法复杂度得到了显著降低。     

衰落环境下一种高能效协作频谱感知算法

在认知无线网络中,对于电池供电的认知设备,如何高效地利用其能量资源极为重要。在将能量效率(能效)定义为认知网络频谱利用效率和平均功率消耗之比的基础上,提出了一种高能效优化算法,在加性高斯白噪声(AWGN)信道、Rayleigh衰落信道和Nakagami衰落信道条件下使融合中心门限达到最优,并求得了最佳的参与协作的用户数。通过蒙特卡洛仿真对认知网络的能效进行了性能评估,结果表明所提算法能有效提升认知网络的能量效率。     

采用相关系数和拟合优度的频谱盲检测

已有的基于拟合优度频谱感知算法具有较好检测性能的前提是假设感知时主用户信号保持不变,这在认知无线电中是很少见的。该文提出一种适用于多天线认知系统的拟合优度盲频谱感知算法。首先,计算不同天线间接收信号的相关系数;其次,对相关系数进行进行适当的非线性变换使其服从学生分布;最后,对变换后的新序列使用侧重右尾检验的Anderson-Darling(RAD)准则进行拟合优度检验。理论分析和仿真表明,所提算法不需要任何先验信息,与基于最大最小特征值之比(MME)、Anderson-Darling(AD)检测算法以及噪声方差已知的能量检测相比,所提算法具有更好的检测性能。      

基于上行多用户大规模MIMO系统能效优化算法

针对上行多用户大规模多输入多输出（MIMO）系统,提出了基于能效优化的资源分配方法。所提方法采用迫零(ZF)接收,以最大化系统能效下界为准则,系统功率消耗考虑电路功率消耗和发射功率消耗2部分,通过联合调整基站端的发射天线数和用户的数据速率来优化能效函数。首先,根据目标函数的性质,证明全局最优速率分配和天线数的存在性和唯一性,然后,根据分数规划的性质,把原始的分数最优化问题转换成减式形式,进而提出一种新的迭代算法。仿真结果表明,所提算法以较少迭代次数取得了接近最优算法的性能。     

Cooperative spectrum sensing in the presence of primary user emulation attack in cognitive radio network: multi-level hypotheses test approach

The inherent nature of cognitive radio (CR) networks has brought new threats to wireless communications. Primary user emulation attack (PUEA) has been widely studied as a serious threat to cooperative spectrum sensing (CSS) in CR networks. In PUEA, a malicious user can obstruct CR users from accessing idle frequency bands by imitating licensed primary user (PU) signal characteristics. The present study introduces a new CSS scheme in the presence of a malicious PUEA based on multi-level hypothesis testing (MLHT). In the proposed method, generalizing from binary hypothesis testing to MLHT, we partition the decision space to four decision options and apply minimum Bayes cost criteria to determine the channel status. We also discuss practical limitation issues that need to be considered when applying the MLHT approach. Simulation results are provided to indicate the performance improvement of the proposed MLHT method against PUEA, compared with the conventional method.     

Cyclostationarity-based cooperative spectrum sensing over imperfect reporting channels

Reliable detection of weak primary user signals is a crucial problem for cognitive radio networks. To address the above issue, cooperative spectrum sensing (CSS) methods based on cyclostationary detection (CD) have been introduced in the literature. In this paper, a soft decision-based CSS method based on the second-order CD at secondary users (SUs) is proposed. The proposed scheme aims to maximize the deflection criterion at the fusion center (FC), while the reporting channels are characterized by Rayleigh fading. To this end, a fusion rule which does not require to know the noise variances of sensing channels is developed. Since the fusion rule assumes the perfect knowledge of channel state information (CSI) of reporting links, it has theoretical significance and provides an upper bound for the performance of cyclostationarity-based CSS. We have also proposed a more practical suboptimum fusion rule and studied its detection performance in the presence of uncertainties in noise variance and channel power gain estimations. Furthermore, in order to be able to evaluate the performance of the CSS, an analytic threshold estimation method has been proposed. Extensive simulation results have been illustrated the robustness of the proposed method compared to the existing cyclostationary detectors.     

Cooperative spectrum sensing for cognitive radio networks in the presence of smart malicious users

Cognitive radio (CR) signaling imposes some threats to the network. One of these common threats is commonly referred to as primary user emulation attack, where some malicious users try to mimic the primary signal and deceive secondary users to prevent them from accessing vacant frequency bands. In this paper, we introduce a smart primary user emulation attacker (PUEA) that sends fake signals similar to the primary signal. We assume a smart attacker, in the sense that it is aware of its radio environment and may choose different transmission strategies and then, we compare it to an always present attacker. In the proposed smart attacker strategy, the occurrence of fake signal is adjusted according to the primary user activity. First, we investigate the received signal at the CR users under such attackers. Then, we formulate and derive cooperative spectrum sensing (CSS) rules for a cognitive network operating in the presence of a PUEA and propose a new spectrum sensing scheme based on energy detection. Simulation results show that our proposed method can mitigate the destructive effect of PUEA in spectrum sensing, compared to conventional energy detection spectrum sensing.     

Cooperative Spectrum Sensing with Adaptive Double-Threshold Based Energy Detector in Cognitive Radio Networks

Spectrum sensing is one of the key functionalities in the implementation of cognitive radio. It is used to sense the unused spectrum in an opportunistic manner. In this paper, we propose an energy detector with adaptive double-threshold for spectrum sensing, to optimize the detection performance at a fixed probability of false alarm $(\text{ P }_\mathrm{f})$ i.e. 0.1, which also overcomes sensing failure problem. In the present work, the detection threshold is made adaptive to the fluctuation of the received signal power in each local detector of cognitive radio (CR) user. Simulation results show that proposed scheme optimizes better detection performance and outperforms both conventional energy detector and cooperative spectrum sensing (CSS) method by 12.8 and 3.3 % at $-$ 8 dB signal to noise ratio (SNR), respectively. While utilizing CSS with proposed adaptive double-threshold scheme, where each CR user use a double threshold detectors for local detection and send detection decisions to fusion center (FC) to give the final decision based on hard decision rule. It is further found that CSS with adaptive double-threshold improves detection performance around 26.8 and 7.6 % as compare to CSS with single threshold and Hierarchical with quantization method at $-$ 10 dB SNR, respectively, under the case when a small number of sensing nodes are used in spectrum sensing.     

A novel approach for energy‐efficient resource allocation in double threshold‐based cognitive radio network

This paper mainly focuses on solving the energy efficiency (EE) maximization problem in double threshold‐based soft decision fusion (SDF) cooperative spectrum sensing (CSS) in the cognitive radio network (CRN). The solution to this objective problem starts with the selection of suitable secondary users (SUs) both for the spectrum sensing and data transmission. Here, energy efficiency is maximized under the constraints of interference to the primary user (PU), an acceptable outage of SUs, the transmission power of the SUs and the probability of false alarm. We propose a novel algorithm called iterative Dinkelbach method (IDM) which jointly optimizes the sensing time and transmission power allocation to the SUs. Further, Lagrangian duality theorem is employed to find the exact power assigned to the SUs. Finally, simulation results are carried out to validate the effectiveness of our proposed scheme by comparing with the other existing schemes. The performance is also analyzed for different system parameters.     

Double‐threshold cooperative detection for cognitive radio based on weighing

In cognitive radio (CR), the single‐threshold cooperative detection is sensitive to the noise power. In this paper, a double‐threshold cooperative detection scheme based on weighed combination is proposed to improve the global detected performance of the cooperative detection. The double thresholds that are decided by the restriction probability are adopted to divide the energy statistics observed by CRs into three subareas, and the detected performance of the CRs locating in the confusion area is fortified through the weighed data fusion by the coordinator. The CRs in the other two areas can make local binary decisions because of their exact sensing performance and then forward their 1‐bit decisions to the coordinator that will combine all the received decisions to give the final decision on the presence of the primary user. In this paper, both the periodic single‐band and wideband cooperative detections are investigated, and the probabilities of spectrum utilization by these two patterns are respectively analyzed. The simulation shows that the detection probability of the proposed scheme is better than that of the single‐threshold cooperative detection with decision fusion but slightly worse than that of the single‐threshold cooperative detection with data fusion. However, the average number of the bits sent to the coordinator by the proposed algorithm is less than that by the data fusion, and it may increase by the decreasing of the restriction probability. The simulation also shows that the periodic wideband sensing can obtain higher spectrum utilization than the periodic single‐band sensing. Copyright © 2012 John Wiley & Sons, Ltd.     

A novel relay-aided centralized cooperative spectrum sensing scheme using radio frequency energy harvesting

In a cooperative spectrum sensing (CSS) network, the primary signal can be used as a radio frequency (RF) source in order to power the energy-constrained sensor nodes of the secondary network. This work presents a novel hybrid model combining an optimal relay selection scheme to incorporate RF energy harvesting in a centralized CSS network. The secondary users, which are equipped with RF energy harvesting capabilities, act as relays in order to forward the sensing information to a fusion center. Here, we have derived an enhanced multi-relay selection strategy to maximize the end-to-end signal-to-noise ratio of the links. Furthermore, a new voting rule is proposed based on the generalized K-out-of-M rule, such that it minimizes our objective error function. The performance analysis of our proposed model is presented with respect to the flexible relay positions. We have used complementary receiver operating characteristic curves for analyzing the detection performance of the CSS model with our derived voting rule. Simulation results using MATLAB show that the proposed model gives a better detection probability and a smaller error rate than some related existing works.     

Detection performance of cooperative spectrum sensing with hard decision fusion in fading channels

In this paper, we investigate the detection performance of cooperative spectrum sensing (CSS) using energy detector in several fading scenarios. The fading environments comprise relatively less-studied Hoyt and Weibull channels in addition to the conventional Rayleigh, Rician, Nakagami-m and log-normal shadowing channels. We have presented an analytical framework for evaluating different probabilities related to spectrum sensing, i.e. missed detection, false alarm and total error due to both of them, for all the fading/shadowing models mentioned. The major theoretical contribution is, however, the derivation of closed-form expressions for probability of detection. Based on our developed framework, we present performance results of CSS under various hard decision fusion strategies such as OR rule, AND rule and Majority rule. Effects of sensing channel signal-to-noise ratio, detection threshold, fusion rules, number of cooperating cognitive radios (CRs) and fading/shadowing parameters on the sensing performance have been illustrated. The performance improvement achieved with CSS over a single CR-based sensing is depicted in terms of total error probability. Further, an optimal threshold that minimises total error probability has been indicated for all the fading/shadowing channels.     

Optimized cooperative spectrum sensing network analysis in nonfading and fading environments

The proposed cooperative spectrum sensing (CSS) network is equipped with multiple antennas and an improved energy detector (IED) scheme at each cognitive radio (CR). Each CR in the network receives the information about the primary user (PU) in the form of binary decisions at multiple antennas. Diversity technique called selection combining (SC) scheme is used at multiple antennas to select the maximum value of sensing information present at multiple antennas. Finally, sensing information will be passed to the fusion center (FC) through reporting channel, and the final decision about PU is made at FC using fusion rules. Initially, we have derived the novel missed detection probability expressions for AWGN channel, Rayleigh, and Rician fading environments. Later, the closed form of optimized expressions for proposed CSS network parameters are derived to achieve an optimal performance. The closed form of optimized expressions such as number of CR users (N_opt ), normalize threshold value (λ_n,opt ), and an arbitrary power of the received signal (p_opt ) are derived under various fading environments. The performance is evaluated using complementary receiver operating characteristics (CROC) and total error rate curves. The MATLAB‐based simulations are evaluated with the strong support of theoretical expressions. Finally, various simulation parameters such as sensing channel SNR, the error rate in reporting channel, threshold value, and number of antennas at each CR are considered in the simulation to show the effect on the performance of proposed CSS network.